What was your journey/career path to your current position?
With a background in behavioral economics I was always interested in exploring data from a behavioral perspective, especially opinions about brands. When I joined Coca-Cola’s CIC team (consumer interaction center - at the time) we started to build out a database tracking brand reputational topics and gradually we began to look at advertising campaigns, looking at how the campaigns resonated on social media. Being relatively new to the industry, I felt I was sitting on a very rich and powerful data source as there was a lot of quality conversation about Coca-Cola, and aside from the noise, a great deal of valuable insights for the business to be aware of.
Ever since, I made it my mission to showcase the value of social intelligence to businesses. Years later, I joined SHARE Creative building our intelligence department. I was quite excited that our CEO placed a huge focus on data powered marketing and social media was a great source to get insights for all types of briefs. We focused on leveraging social media conversion data and with the help of our data science team, we were able to evolve our research practice and work with some of the most advanced researchers in the industry. Today we help businesses like Microsoft transform unstructured data into knowledge and insights answering some of the most complex and pertinent questions with the help of social intelligence.
What's your proudest achievement of your career to date?
Working with Microsoft and helping them to set up their social intelligence practice.
Being selected as an agency partner by Microsoft to co-define the standards of social intelligence research and becoming their innovation partner was definitely a career highlight. Pitching over 3 years ago, it has been an incredible journey to where we are now and what we've achieved together.
What does social intelligence mean to you?
Analyzing social media mentions with rigor and in a methodological way, understanding how to take the data further aligned with the phenomenon that we want to research. This also includes the appreciation of 'letting the data tell the story'.
The difference between social listening and social intelligence is that social listening is monitoring what is happening and how the conversation is evolving, but social intelligence means analyzing posts with a defined methodology that is aligned with the principles of academic research.
Playing into the strengths of social intelligence means being able to extract insights beyond the actual question and uncover opportunities that we might not have anticipated as per the briefs or research questions.
What's been the biggest challenge you’ve faced while trying to get brands to integrate social intelligence within their growth strategy?
Approaching social intelligence with the same mindset as traditional research is one of the biggest challenges to overcome. Social intelligence requires an open brief and while it comes with many strengths, our capabilities to analyze always depend on what conversation is naturally occurring. Unlike with survey methodologies where we can ask very pointed questions, social intelligence is most valuable if we approach questions in an exploratory manner. We have been tackling this by suggesting an audit and describing the type of data set that we have at hand which builds trust in social intelligence and manages expectations. It also shows what's possible and how to create research questions that deliver valuable insights for brands to capitalize on.
What do you think is the biggest missed opportunity for social intelligence?
Leveraging social intelligence for business questions beyond marketing, communications or advertising. In the marketing industry we are often looking to social media for insights to inform a strategy but social intelligence can aid business decisions to help companies grow. This means integrating social intelligence at an early stage to be able to make decisions e.g. about marketing investments / product or services developments or uncovering new market opportunities before going too deep into planning and tactics.
For product and service developments social intelligence is a great source of information to understand unmet needs; when developing new products or improving existing ones, why not get inspiration from the often very passionate community?
What's on the cards for you and your team/organisation in 2022?
Innovation and pioneering work are the key drivers of our department and with that in mind we have a few different areas in the pipe that we are building out in 2022.
Sina Weibo & Co - We are expanding our social intelligence capabilities to integrate platforms from the Asian landscape to have access to more data from an innovation perspective as well as research.
The art of query writing - We are developing a query library including a best practice framework to ensure consistency in data querying. One of my favorite things about social intelligence is that the data can be sliced and diced in so many different ways. Overlaying queries to uncover unmet needs is just one example that highlights the importance of great query writing. Every analysis in social intelligence is based on the foundation of what type of conversation we are going to pull into a listening platform.
Measuring Influence - Developing new methodologies to measure impact beyond performance metrics from social media, such as reach and impressions. This includes understanding how authors are connected within a community and what impact they have within a topic of interest.
How do you see social intelligence and its use evolving?
Social intelligence is often used to complement traditional research however in the future it will increasingly be the starting point and traditional research will be used to explore very specific questions rather than the other way around.
Due to its strengths in uncovering the unforeseeable, social intelligence will be considered earlier in the research design, defining the landscape and what we should explore next.
The practice will become more methodological, establishing more trust in the data due to the rigor and proof of concepts.
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